{"type":"ScholarlyArticle","title":"Learning Dissemination Strategies for External Sources in Opinion Dynamic Models with Cognitive Biases","authors":[{"name":"Abdullah Al Maruf","slug":"abdullah-al-maruf","given":"Abdullah","family":"Al Maruf","affiliation":"Network Security Lab , Department of Electrical & Computer Engineering , University of Washington"},{"name":"Luyao Niu","slug":"luyao-niu","given":"Luyao","family":"Niu","affiliation":"Network Security Lab , Department of Electrical & Computer Engineering , University of Washington"},{"name":"Bhaskar Ramasubramanian","slug":"bhaskar-ramasubramanian","given":"Bhaskar","family":"Ramasubramanian","affiliation":"Electrical and Computer Engineering , Western Washington University"},{"name":"Andrew Clark","slug":"andrew-clark","given":"Andrew","family":"Clark","affiliation":"Electrical & Systems Engineering , Washington University in St. Louis"},{"name":"Radha Poovendran","slug":"radha-poovendran","given":"Radha","family":"Poovendran","affiliation":"Network Security Lab , Department of Electrical & Computer Engineering , University of Washington"}],"abstract":"The opinions of members of a population are influenced by opinions of their peers, their own predispositions, and information from external sources via one or more information channels (e.g., news, social media). Due to individual cognitive biases, the perceptual impact of and importance assigned by agents to information on each channel can be different. In this paper, we propose a model of opinion evolution that uses prospect theory to represent perception of information from the external source along each channel. Our prospect-theoretic model reflects traits observed in humans such as loss aversion, assigning inflated (deflated) values to low (high) probability events, and evaluating outcomes relative to an individually known reference point. We consider the problem of determining information dissemination strategies for the external source to adopt in order to drive opinions of individuals towards a desired value. However, computing a strategy faces a challenge that agents' initial predispositions and functions characterizing their perceptions of information disseminated might be unknown. We overcome this challenge by using Gaussian process learning to estimate these unknown parameters. When the external source sends information over multiple channels, the problem of jointly selecting optimal dissemination strategies is in general, combinatorial. We prove that this problem is submodular, and design near-optimal dissemination algorithms. We evaluate our model on three different widely used large graphs that represent real-world social interactions. Our results indicate that the external source can effectively drive opinions towards a desired value when using prospect-theory based dissemination strategies.","doi":"10.24963/ijcai.2023/1","url":"https://ijcai.org/proceedings/2023/1","pdf":"https://ijcai.org/proceedings/2023/0001.pdf","markdown":"https://ijcai.org/proceedings/2023/1.md","bibtex":"https://ijcai.org/proceedings/2023/bibtex/1","volume":{"slug":"2023","title":"Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2023","url":"https://ijcai.org/proceedings/2023/","year":2023,"location":"Macao, SAR","dates":"19-25 August 2023","editors":"Edith Elkind","isbn":"978-1-956792-03-4","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2023"},"section":"Agent-based and Multi-agent Systems","track":"Main Track","number":1,"pages":{"first":3,"last":11},"keywords":["Agent-based and Multi-agent Systems: MAS: Agent theories and models","Agent-based and Multi-agent Systems: MAS: Coordination and cooperation","Agent-based and Multi-agent Systems: MAS: Other"],"videos":[],"references":[{"position":1,"raw":"[Acemoglu and Ozdaglar, 2011] Daron Acemoglu and Asuman Ozdaglar. 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